from great_tables import GT, data, loc, style
from shiny import App, reactive, ui

import pointblank as pb
from pointblank.shiny import pb_server, pb_ui

CARS_ID = "cars_validation"


app_ui = ui.page_fluid(
    ui.input_slider("num_rows", "Rows in Preview (GT Cars only)", 5, 50, 10, step=5),
    ui.navset_tab(
        ui.nav_panel(
            ui.h4("GT Cars Data"),
            ui.input_select("select_drivetrain", "Select Drivetrain Type", ["rwd", "awd"]),
            pb_ui(CARS_ID, title="GT Cars Data Validation"),
        ),
    ),
)


def server(user_in, output, session):
    @reactive.calc
    def car_data():
        drivetrain = user_in.select_drivetrain()
        return data.gtcars.assign(hp=lambda df: df["hp"]).loc[
            lambda df: df["drivetrain"] == drivetrain
        ]

    @reactive.calc
    def cars_validator() -> pb.Validate:
        schema = pb.Schema(
            columns=[
                ("mfr", "object"),
                ("model", "object"),
                ("year", "int64"),
                ("trim", "object"),
                ("bdy_style", "object"),
                ("hp", "float64"),
                ("hp_rpm", "float64"),
                ("trq", "float64"),
                ("trq_rpm", "float64"),
                ("mpg_c", "float64"),
                ("mpg_h", "float64"),
                ("drivetrain", "object"),
                ("trsmn", "object"),
                ("ctry_origin", "object"),
                ("msrp", "float64"),
            ]
        )
        valid = (
            pb.Validate(car_data(), thresholds=(0, 0, 0), label="Cars Validation")
            .col_schema_match(schema, complete=True)
            .col_vals_ge("hp", 0)
            .col_vals_ge("hp_rpm", 5500)
            .col_vals_in_set("bdy_style", ["coupe", "sedan", "convertible"])
            .col_vals_in_set("ctry_origin", ["Germany", "Italy", "United Kingdom", "United States"])
            .interrogate()
        )
        return valid

    @reactive.calc
    def cars_table() -> GT:
        return (
            GT(car_data().head(user_in.num_rows()).reset_index())
            .tab_style(style.text(weight="bold"), loc.column_header())
            .cols_hide("index")
            .fmt_currency("msrp", use_subunits=False)
            .cols_label(
                {
                    "mfr": "Make",
                    "model": "Model",
                    "year": "Year",
                    "trim": "Package",
                    "bdy_style": "Body",
                    "drivetrain": "Drivetrain",
                    "trsmn": "Transmission",
                    "ctry_origin": "Country",
                    "msrp": "MSRP",
                    "hp": "Power ({{hp}})",
                    "hp_rpm": "Engine Speed @ Max. Power ({{rev / min}})",
                    "trq": "Torque ({{ft-lbs}})",
                    "trq_rpm": "Engine Speed @ Max. Torque ({{rev / min}})",
                    "mpg_c": "City",
                    "mpg_h": "Highway",
                }
            )
            .opt_stylize()
        )

    _ = pb_server(
        CARS_ID,
        validator=cars_validator  # reactive calc that defines the validation,
        display_table=cars_table  # optional reactive calc that returns a GT of the dataset
)


app = App(app_ui, server)